Collaboration between academic institutions and business corporations is about discovering ways in which both parties benefit from developing such a relationship. This relationship might be simply in terms of preparing students to become productive employees, but perhaps more importantly the research work that takes place in universities can be used to inform and improve products and services in industry.
What are the essential elements that make collaboration between academia and industry possible? Where does one begin? How is this process nurtured and developed?
Senior statisticians and administrators in academia and industry have been brought together to share examples that will help to develop strong connections that provide context for academic pursuits but that also help to impact the bottom line in business.
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The program for this session will be organized as follows:
12:00-12:05 Opening remarks
Sumanta Basu, Assistant Professor atCornell University
12:05-12:20 Rebecca Doerge, Dean of the Mellon College of Science at Carnegie Mellon University
“Establishing a productive collaboration and engagement between academia and industry so that everyone gets what they need”
12:20-12:35 Sam Woolford, Professor Emeritus of Statistics at Bentley University
12:35-12:50 L.J. Wei, Professor of Biostatistics at Harvard University
12:50-1:05 Victor Lo, Head of Data Science & Artificial Intelligence, Workplace Investing, Fidelity Investments
“Multiple Pathways to Collaboration Between Academia and Industry in Data Science & Statistics”
Rebecca Doerge, Ph.D. is the Glen de Vries Dean of the Mellon College of Science at Carnegie Mellon University. Prior to joining both the Department of Statistics and the Department of Biology at Carnegie Mellon University she was the Trent and Judith Anderson Distinguished Professor of Statistics at Purdue University. Dean Doerge joined Purdue University in 1995 and held a joint appointment between the Colleges of Agriculture (Department of Agronomy) and Science (Department of Statistics) until her departure from Purdue University. Professor Doerge's research program is focused on Statistical Bioinformatics, a component of bioinformatics that brings together many scientific disciplines into one arena to ask, answer, and disseminate biologically interesting information in the quest to understand the ultimate function of DNA and epigenomic associations. Rebecca is the recipient the many prestigious teaching and research awards. She is an elected Fellow of the American Statistical Association (2007), an elected Fellow of the American Association for the Advancement of Science (2007), and a Fellow of the Committee on Institutional Cooperation (CIC; 2009). She is the Chair-Elect of the AAAS Section U. Dean Doerge has published over 130 scientific articles, published two books, and graduated 25 Ph.D. students.
Sam Woolford, Ph.D. is a Professor Emeritus of Statistics at Bentley University and the Founding Director of Bentley’s Center for Quantitative Analysis, which provides business analytics consulting services for external organizations. His research interests focus on the application of statistical modeling to real world problems. Professor Woolford has spent over 25 years at global consulting firms, building and managing analytics groups to help clients solve complex business problems, improve performance and enhance their competitive position through data analysis and statistical modeling. He has applied statistical methods and operations research to market research, litigation support, customer economics, operations analysis, performance metrics, modeling and simulation.
L.J. Wei is a professor of Biostatistics at Harvard University. Before joining Harvard, he was a professor at University of Wisconsin, University of Michigan, and George Washington University. His main research interest is in the clinical trial methodology, especially in design, monitoring and analysis of studies. He has developed numerous novel statistical methods which are utilized in practice. He received the prestigious Wald Medal in 2009 from the American Statistical Association for his contribution to clinical trial methodology. He is a fellow of American Statistical Associating and Institute of Mathematical Statistics. In 2014, to honor his mentorship, Harvard School of Public Health established a Wei-family scholarship to support students studying biostatistics. His recent research area is concentrated on translational statistics, the personalize medicine under the risk-benefit paradigm via biomarkers and revitalizing clinical trial methodology. He has more than 200 publications and served on numerous editorial and scientific advisory boards. L. J. Wei has extensive working experience in regulatory science for developing and evaluating new drugs/devices.
Victor Lo, Ph.D. is a seasoned Big Data, Marketing, Risk, and Finance leader & innovator with over two decades of extensive consulting and corporate experience employing data-driven solutions in a wide variety of business areas, including Customer Relationship Management, Market Research, Advertising Strategy, Risk Management, Financial Econometrics, Insurance, Product Development, Transportation, Healthcare, and Human Resources. He is actively engaged with Big Data Analytics, causal inference, and is a pioneer of Uplift/True-lift modeling, a key subfield of data science that has been applied to areas as marketing, political election, and medicine. Victor has served as the manager of quantitative teams in multiple organizations. He is currently A.I. and Data Science Center of Excellence Leader, Workplace Investing, Fidelity Investments. Previously he managed advanced analytics teams in Personal Investing, Corporate Treasury, Managerial Finance, and Healthcare and Total Well-being at Fidelity Investments. Prior to Fidelity, he was VP and Manager of Modeling and Analysis at FleetBoston Financial (now part of Bank of America), and Senior Associate at Mercer Management Consulting (now Oliver Wyman).
Sumanta Basu, Ph.D., (Assistant Professor, Shayegani Bruno Family Faculty Fellow, Department of Statistics and Data Science, Department of Computational Biology, Cornell University).